Working papers results

Dynamic Stochastic General Equilibrium (DSGE) models are now con-
sidered attractive by the profession not only from the theoretical perspec-
tive but also from an empirical standpoint. As a consequence of this
development, methods for diagnosing the fit of these models are being
proposed and implemented. In this article we illustrate how the concept
of statistical identification, that was introduced and used by Spanos(1990)
to criticize traditional evaluation methods of Cowles Commission models,
could be relevant for DSGE models. We conclude that the recently pro-
posed model evaluation method, based on the DSGE - VAR(λ), might not satisfy
the condition for statistical identification. However, our appli-
cation also shows that the adoption of a FAVAR as a statistically identified
benchmark leaves unaltered the support of the data for the DSGE model
and that a DSGE-FAVAR can be an optimal forecasting model.

The paper explores the determinants of yield differentials between sovereign
bonds in the Euro area. There is a common trend in yield differentials, which
is correlated with a measure of aggregate risk. In contrast, liquidity differentials
display sizeable heterogeneity and no common factor. We propose a simple model
with endogenous liquidity demand, where a bond's liquidity premium depends both
on its transaction cost and on investment opportunities. The model predicts that
yield differentials should increase in both liquidity and risk, with an interaction
term of the opposite sign. Testing these predictions on daily data, we find that
the aggregate risk factor is consistently priced, liquidity differentials are priced for
a subset of countries, and their interaction with the risk factor is in line with the
model's prediction and crucial to detect their effect.

We estimate the effect of political regime transitions on growth with semi-parametric methods, combining difference in differences with
matching, that have not been used in macroeconomic settings. Our semi-parametric estimates suggest that previous parametric estimates
may have seriously underestimated the growth effects of democracy. In particular, we find an average negative effect on growth of leav-
ing democracy on the order of -2 percentage points implying effects on income per capita as large as 45 percent over the 1960-2000 panel.
Heterogenous characteristics of reforming and non-reforming countries appear to play an important role in driving these results.

Development accounting exercises based on an aggregate production function find tech-
nology is biased in favor of a country's abundant production factors. We provide an expla-
nation to this finding based on the Heckscher-Ohlin model. Countries trade and specialize
in the industries that use intensively the production factors they are abundantly endowed
with. For given factor endowment ratios, this implies smaller international differences in
factor price ratios than under autarky. Thus, when measuring the factor bias of technol-
ogy with the same aggregate production function for all countries, they appear to have
an abundant-factor bias in their technologies.

In this paper we analyze a novel dataset of Business and Consumer Surveys, using dynamic
factor techniques, to produce composite coincident indices (CCIs) at the sectoral
level for the European countries and for Europe as a whole. Few CCIs are available
for Europe compared to the US, and most of them use macroeconomic variables and
focus on aggregate activity. However, there are often delays in the release of macroeconomic
data, later revisions, and differences in the definition of the variables across
countries, while the surveys are timely available, not subject to revision, and fully comparable
across countries. Moreover, there are substantial discrepancies in activity at
the sectoral level, which justifies the interest in a sectoral disaggregation. Compared
to the Confidence Indicators produced by the European Commission, which are based
on a simple average of the aggregate survey answers, we show that factor based CCIs,
using survey answers at a more disaggregate level, produce higher correlation with the
reference series for the majority of sectors and countries.

Monitoring the current status of the economy is quite relevant for policy making
but also for the decisions of private agents, consumers and firms. Since it is difficult
to identify a single variable that provides a good measure of current economic
conditions, it can be preferable to consider a combination of several coincident indicators,
i.e., a composite coincident index (CCI). In this paper, we review the main
statistical techniques for the construction of CCIs, propose a new pooling-based
method, and apply the alternative techniques for constructing CCIs for the largest
European countries in the euro area and for the euro area as a whole. We find that
different statistical techniques yield comparable CCIs, so that it is possible to reach
a consensus on the status of the economy.

This paper addresses the issue of forecasting the term structure.
We provide a unified state-space modelling framework that encom-
passes different existing discrete-time yield curve models. within such
framework we analyze the impact on forecasting performance of two
crucial modelling choices, i.e. the imposition of no-arbitrage restric-
tions and the size of the information set used to extract factors. Using
US yield curve data, we find that: a. macro factors are very useful in
forecasting at medium/long forecasting horizon; b. financial factors
are useful in short run forecasting; c. no-arbitrage models are effec-
tive in shrinking the dimensionality of the parameter space and, when
supplemented with additional macro information, are very effective in
forecasting; d. within no-arbitrage models, assuming time-varying risk
price is more favorable than assuming constant risk price for medium
horizon-maturity forecast when yield factors dominate the informa-
tion set, and for short horizon and long maturity forecast when macro
factors dominate the information set; e. however, given the complex-
ity and the highly non-linear parameterization of no-arbitrage models,
it is very difficult to exploit within this type of models the additional
information offered by large macroeconomic datasets.

Empirical investigations of the effects of fiscal policy shocks share
a common weakness: taxes, government spending and interest rates
are assumed to respond to various macroeconomic variables but not
to the level of the public debt; moreover the impact of fiscal shocks
on the dynamics of the debt-to-GDP ratio are not tracked. We ana-
lyze the effects of fiscal shocks allowing for a direct response of taxes,
government spending and the cost of debt service to the level of the
public debt. We show that omitting such a feedback can result in
incorrect estimates of the dynamic effects of fiscal shocks. In par-
ticular the absence of an effect of fiscal shocks on long-term interest
rates-a frequent finding in research based on VAR's that omit a debt
feedback-can be explained by their mis-specification, especially over
samples in which the debt dynamics appears to be unstable. Using
data for the U.S. economy and the identification assumption proposed
by Blanchard and Perotti (2002) we reconsider the effects of fiscal
policy shocks correcting for these shortcomings.

monetary policy in an estimated, semi-structural, small-open-economy model of the
U.K. Compared to the closed economy, the presence of an exchange rate channel for
monetary policy not only produces new trade-offs for monetary policy, but it also
introduces an additional source of specification errors. We find that exchange rate
shocks are an important contributor to volatility in the model, and that the exchange
rate equation is particularly vulnerable to model misspecification, along with the
equation for domestic inflation. However, when policy is set with discretion, the
cost of insuring against model misspecification appears reasonably small.

Conventional economic wisdom suggests because of the aging process, social security
systems will have to be retrenched. In particular, retirement age will have to be largely
increased. Yet, is this policy measure feasible in OECD countries? Since the answer
belongs mainly to the realm of politics, I evaluate the political feasibility of postponing
retirement under aging in France, Italy, the UK, and the US. Simulations for the year
2050 steady state demographic, economic and political scenario suggest that retirement
age will be postponed in all countries, while the social security contribution rate will
rise in all countries, but Italy. The political support for increasing the retirement age
stems mainly from the negative income effect induced by aging, which reduces the
profitability of the existing social security system, and thus the individuals net social
security wealth.